Triple

T13305927
Position Surface form Disambiguated ID Type / Status
Subject Maarten ’t Hart E316935 entity
Predicate notableWork P4 FINISHED
Object De unster
De unster is a novel by Dutch author Maarten ’t Hart, known for its psychologically rich storytelling and exploration of human relationships.
E1032030 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: De unster | Statement: [Maarten ’t Hart, notableWork, De unster]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: De unster
Context triple: [Maarten ’t Hart, notableWork, De unster]
  • A. Udelnaya
    Udelnaya is a residential neighborhood and railway station area in the northern part of Saint Petersburg, Russia.
  • B. Derbystar
    Derbystar is a German sports equipment brand best known for producing high-quality footballs used in professional leagues and competitions.
  • C. Uden
    Uden is a town in the southern Netherlands known for its location in the province of North Brabant and its proximity to nature reserves and regional industry.
  • D. Undset
    Undset is the surname of Sigrid Undset, the Norwegian novelist and Nobel Prize in Literature laureate renowned for her medieval trilogy "Kristin Lavransdatter."
  • E. Unsuri
    Unsuri was a prominent 11th-century Persian court poet renowned for his panegyrics and refined style, serving as a leading literary figure in the Ghaznavid era.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: De unster
Triple: [Maarten ’t Hart, notableWork, De unster]
Generated description
De unster is a novel by Dutch author Maarten ’t Hart, known for its psychologically rich storytelling and exploration of human relationships.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: De unster
Target entity description: De unster is a novel by Dutch author Maarten ’t Hart, known for its psychologically rich storytelling and exploration of human relationships.
  • A. Udelnaya
    Udelnaya is a residential neighborhood and railway station area in the northern part of Saint Petersburg, Russia.
  • B. Derbystar
    Derbystar is a German sports equipment brand best known for producing high-quality footballs used in professional leagues and competitions.
  • C. Uden
    Uden is a town in the southern Netherlands known for its location in the province of North Brabant and its proximity to nature reserves and regional industry.
  • D. Undset
    Undset is the surname of Sigrid Undset, the Norwegian novelist and Nobel Prize in Literature laureate renowned for her medieval trilogy "Kristin Lavransdatter."
  • E. Unsuri
    Unsuri was a prominent 11th-century Persian court poet renowned for his panegyrics and refined style, serving as a leading literary figure in the Ghaznavid era.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d806b40ab4819094adf6c374f4811a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d990a76adc8190ab9abcdb79a21ca8 completed April 11, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69f716e3617081909eea9989cf5e7b30 completed May 3, 2026, 9:35 a.m.
NEDg Description generation batch_69f7179da5488190a10acadbf60ea470 completed May 3, 2026, 9:38 a.m.
NED2 Entity disambiguation (via description) batch_69f71847e7308190ac6f59a7dcafa452 completed May 3, 2026, 9:41 a.m.
Created at: April 9, 2026, 9:28 p.m.